Title :
Lexicon-Free, Novel Segmentation of Online Handwritten Indic Words
Author :
Sundaram, Suresh ; Ramakrishan, A.G.
Author_Institution :
Dept. of Electr. Eng., Indian Inst. of Sci., Bangalore, India
Abstract :
Research in the field of recognizing unlimited vocabulary, online handwritten Indic words is still in its infancy. Most of the focus so far has been in the area of isolated character recognition. In the context of lexicon-free recognition of words, one of the primary issues to be addressed is that of segmentation. As a preliminary attempt, this paper proposes a novel script-independent, lexicon-free method for segmenting online handwritten words to their constituent symbols. Feedback strategies, inspired from neuroscience studies, are proposed for improving the segmentation. The segmentation strategy has been tested on an exhaustive set of 10000 Tamil words collected from a large number of writers. The results show that better segmentation improves the overall recognition performance of the handwriting system.
Keywords :
handwritten character recognition; image segmentation; vocabulary; word processing; Tamil words; feedback strategies; isolated character recognition; lexicon-free segmentation; lexicon-free word recognition; neuroscience studies; online handwritten Indic word segmentation; unlimited vocabulary recognition; Character recognition; Databases; Feature extraction; Handwriting recognition; Knowledge based systems; Neuroscience; Support vector machines; Dominant overlap Segmentation (DOS); Feedback segmentation (FS); Online Tamil symbol recognition; Stroke Group; Support Vector Machine (SVM);
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
DOI :
10.1109/ICDAR.2011.237
